An evaluation of classical steady-state off-line linear parameter estimation methods applied to chiller performance data

T. Agami Reddy, Klaus K. Andersen

Research output: Contribution to journalArticlepeer-review

54 Scopus citations

Abstract

The objective of this paper is to evaluate different inverse methods with application to off-line model parameter estimation using data from a field-operated chiller. In HVAC&R data analysis, there is sometimes a need to evaluate and use estimation techniques that are more subtle than the ordinary least square (OLS) method. One example is in fault detection and diagnosis of HVAC&R equipment and systems using performance data obtained from field monitoring. By identifying a better performance model, the fault detection process is more likely to be refined and accurate. In this paper a number of exploratory, diagnostic, and classical estimation methods are reviewed to determine the circumstances in which they are likely to be superior to the OLS method. These methods are then evaluated using monitored data from a field-operated chiller. This study provides a reference on parameter estimation methods for the HVAC&R community.

Original languageEnglish (US)
Pages (from-to)101-124
Number of pages24
JournalHVAC and R Research
Volume8
Issue number1
DOIs
StatePublished - Jan 2002
Externally publishedYes

ASJC Scopus subject areas

  • Building and Construction

Fingerprint

Dive into the research topics of 'An evaluation of classical steady-state off-line linear parameter estimation methods applied to chiller performance data'. Together they form a unique fingerprint.

Cite this